Deficiencies or not [Study As­sess­ment]

posted by zizou – Plzeň, Czech Republic, 2021-01-31 02:07 (1233 d 03:45 ago) – Posting: # 22195
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Dear Helmut.

3. ANOVA analysis of variance showed statistically significant (at a 5% significance level) differences in AUC(0-t) between investigational products, which further exacerbated the uncertainty about fulfillment of the bioequivalence criteria.

The statistically significant formulation effect for AUC(0-t) is quite common. The sample size is usually estimated with intra-subject CV of Cmax (as it is usually higher than of AUC(0-t)).

To continue with your example:
Assumed intra-subject CV of Cmax = 25% -> with assumed PE of 95% for target power 90%: n = 38
Assumed intra-subject CV of AUC(0-t) e.g. 10%
When assumed parameters used for sample size estimation will be theoretically observed in the study, i.e. the observed GMR will be 95% and observed intra-subect CV will be 10%, we will get 90% CI equal to 91.40-98.74% and statistically significant formulation effect (at a 10% significance level).
If the 90% CI does not contain 100%, the p value will always be <0.1 but how it could further exacerbated the uncertainty about fulfillment of the bioequivalence criteria? (Question for regulators.)

  100% not within CI           :  5.76% (∆ stat. significant)

I just want to point that it's observed more often for AUC(0-t) than for Cmax and it would be interesting to know the percentage of that also for AUC(0-t) with lower variability. ;)

2. Lack of a posteriori data on the power...

The only good thing on this point is that the regulators believe that test and reference IMPs are bioequivalent. (As they deal with power.)
Posteriori power is never ending story. The question on the power should be raised to the protocol, if it is addressed to the report, it is just a suggestion for future projects.
Additionaly You can remind them what the low power means: With lower power, the type II error (sponsor's risk) is higher - it means that the bioequivalent preparations could be assessed wrongly as not bioequivalent with higher probability. The regulators should sleep well with higher type II error (unless the study was designed for e.g. 50% power from the start - but such protocols should be rejected).

I wish the regulators would be interested also in the type I error - it would mean that regulators do not believe that test and reference IMPs are bioequivalent. The probability of approving non-bioequivalent test product should be up to 5%. I noticed several studies which suprised me more than this deficiency letter. E.g. by using:

Btw. I am also sure you will get approval. As even studies where 90% CI was (partly) outside 80-125% were approved at the end.

Best regards,

PT Frustration - not related to vaccine

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